Accelerated aging in bipolar disorder: A comprehensive review of molecular findings and their clinical implications

Journal Pre-proof Accelerated aging in bipolar disorder: a comprehensive review of molecular findings and their clinical implications Gabriel R. Fries, Madeline J. Zamzow, Taylor Andrews, Omar Pink, Giselli Scaini, Joao Quevedo

PII:

S0149-7634(19)30993-5

DOI:

https://doi.org/10.1016/j.neubiorev.2020.01.035

Reference:

NBR 3680

To appear in:

Neuroscience and Biobehavioral Reviews

Received Date:

25 October 2019

Revised Date:

11 January 2020

Accepted Date:

29 January 2020

Please cite this article as: Fries GR, Zamzow MJ, Andrews T, Pink O, Scaini G, Quevedo J, Accelerated aging in bipolar disorder: a comprehensive review of molecular findings and their clinical implications, Neuroscience and Biobehavioral Reviews (2020), doi: https://doi.org/10.1016/j.neubiorev.2020.01.035

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Accelerated aging in bipolar disorder: a comprehensive review of molecular findings and their clinical implications Gabriel R. Friesa,b,c*, Madeline J. Zamzowa, Taylor Andrewsa, Omar Pinka, Giselli Scainia, Joao Quevedoa,c,d,e

a

Translational Psychiatry Program, Louis A. Faillace, MD, Department of Psychiatry &

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Behavioral Sciences, The University of Texas Health Science Center at Houston. 1941 East Rd,

b

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77054 Houston, TX.

Center for Precision Health, School of Biomedical Informatics, The University of Texas Health

Neuroscience Graduate Program, The University of Texas MD Anderson Cancer Center

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c

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Science Center at Houston. 7000 Fannin St, 77030 Houston, TX.

UTHealth Graduate School of Biomedical Sciences, Houston, TX, USA. Translational Psychiatry Laboratory, Graduate Program in Health Sciences, University of

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d

Southern Santa Catarina (UNESC), Criciúma, SC, Brazil e

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Center of Excellence in Mood Disorders, Department of Psychiatry & Behavioral Sciences, The

University of Texas Health Science Center at Houston. 1941 East Rd, 77054 Houston, TX.

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Highlights 

Patients with bipolar disorder (BD) show signs of premature aging;

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Accelerated biological aging processes have been shown in BD;

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Patients with BD have shown alterations in levels of biological clocks;

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Common altered clocks include telomere length, oxidative stress, and inflammation;

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BD shows epigenetic aging and mitochondrial DNA copy number alterations.

Abstract Bipolar disorder (BD) has been associated with clinical signs of accelerated aging, which potentially underlies its association with several age-related medical conditions, such as hypertension, metabolic imbalances, dementia, and cancer. This paper aims to comprehensively review evidence of biological aging in BD and explore findings and controversies related to

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common biological clocks in patients, including telomere length, DNA methylation,

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mitochondrial DNA copy number, inflammation, and oxidative stress. Our results suggest a

complex interplay between biological markers and a potential key role of environmental factors,

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such as childhood trauma and psychological stress, in determining premature aging in patients.

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Moreover, given its multifactorial nature, our summary evidences the need for further studies incorporating clinical evidence with biomarkers of accelerated aging in BD. Results of this

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review strongly suggest BD as an accelerated aging disease seen in both clinical and molecular aspects. Understanding the pathophysiology of aging in BD may ultimately lead to identification

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of pathways that can be targeted for prevention of premature aging in patients and early onset of aging-related conditions.

Keywords: bipolar disorder; mania; depression; aging; telomere length; DNA methylation;

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epigenetics; mtDNA; oxidative stress; inflammation

1. Introduction Bipolar disorder (BD) is a chronic and often severe mental illness affecting around 1 %

of the population (Merikangas et al., 2011) that is typically associated with episodic changes in

energy levels, mood states, and changes in cognitive abilities (Vieta et al., 2018). BD has an average age at onset of 20 years old (Vieta et al., 2018), and with each additional mood episode, patients tend to experience an increased severity of symptoms and episodes, as well as an increased risk for recurrence (Kessing and Andersen, 2017). Diagnosis of type I BD (BD-I, its most severe form) requires a person to have experienced at least one manic episode, which is typically characterized by a decreased need for sleep, rapid thinking, acting spontaneously on

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ideas, among other symptoms (Grande et al., 2016). Depressive episodes are also a feature of BD

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and are commonly characterized by an increased demand for sleep, a loss of interest in activities, difficulty thinking, and several other symptoms (Grande et al., 2016). Men and women tend to

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have similar ages of onset, number of suicide attempts, as well as number and length of mood

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episodes (Kawa et al., 2005). In addition, comorbidity is high in BD (Spoorthy et al., 2019), with BD-I patients frequently showing comorbidity with other axis 1, substance use, and anxiety

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disorders (Krishnan, 2005).

There is strong evidence to suggest BD as a disease of accelerated aging (Rizzo et al.,

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2014). Older patients with BD are significantly more likely to present decreased cognitive function compared to age-matched healthy controls (Gildengers et al., 2009). Furthermore, Yang and colleagues (2018) demonstrated that those with BD-I have significantly higher levels of growth differentiation factor 15 (GDF-15), a biomarker of aging, with higher GDF-15 levels

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being associated with a longer length of illness, as well (Yang et al., 2018). BD as a condition of accelerated aging is also supported by evidence suggesting that some medications used to treat BD may be protective against accelerated aging effects. For instance, Martinsson and colleagues (2013) reported a positive correlation between duration of lithium treatment, the most commonly used mood stabilizer, and telomere length (Martinsson et al., 2013). Additionally, they found that

BD-I patients who responded clinically to lithium had longer telomere lengths than those who did not. Finally, Huzayyin and colleagues (2014) also found that lithium treatment led to a decrease in global DNA methylation in BD patients (Huzayyin et al., 2014), a marker that has also been recently associated with aging (Johnson et al., 2012). Overall, existing evidence points to the provoking possibility of treating BD by preventing or reversing the accelerated aging effects of the disease. However, the specific effects

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induced by the disorder, its comorbidities, and the treatment on either determining or preventing

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premature aging in patients is still largely unknown. To address these gaps in the literature we aimed to comprehensively review the following three topics: (i) the differences in markers of

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biological aging in multiple tissues of patients with BD compared to healthy controls (focusing

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on aging of the whole individual and not specifically of the central nervous system); (ii) the association between markers of biological aging and endophenotypes of illness (such as

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symptoms and length of illness) in patients with BD; and finally, (iii) the in vivo effects of BD

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treatment on biological markers of aging.

2. Clinical evidence of premature aging in BD While this review will focus on biomarkers of accelerated aging in BD, there is also substantial clinical evidence of premature aging in those with the disorder (Table 1). For

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instance, BD has been associated with a steeper age-related decline in both executive function and cognitive control compared to healthy subjects (Seelye et al., 2019), suggesting that patients with BD may be more likely to experience the cognitive effects of accelerated aging than healthy individuals. Information processing speed, another cognitive indicator of aging, has been shown to be significantly decreased in patients with BD (Gildengers et al., 2007), as well. Additionally,

BD has been associated with changes in brain structure commonly associated with aging, such as ventricular enlargement, loss of grey matter in the cerebellum and hippocampus, decrease in the volume of the prefrontal cortex, and variation in the size of the amygdala (Roda et al., 2015). Finally, BD has also been associated with increased cardiovascular risk score and rates of agingrelated conditions, such as hypertension, metabolic imbalances, dementia, and cancer (clinical markers of aging outside the cognitive realm) (Rizzo et al., 2014; Toma et al., 2019). Overall, the

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variety of conditions and systems affected suggests that BD may be associated with an

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acceleration of many of the mechanisms that underlie the chronological processes associated

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with aging.

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3. Biomarkers of aging: definitions and examples

To begin our discussion of biomarkers of aging in BD it is important to first take a step

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back and define the term “biomarker of aging”. The American Federation for Aging Research (AFAR) has outlined the following criteria to describe it: (1) it must predict the rate of aging; (2)

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it must monitor a basic process that underlies the aging process (and not the effects of disease); (3) it must be able to be tested repeatedly without harming the person; and (4) it must be something that works in humans and in laboratory animals (Xia et al., 2017). In this review, we will initially address biomarkers of aging in general and then narrow our focus to their reported

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associations with BD.

Several biomarkers have been used for the study of aging, include those related to

telomere length, DNA repair, circulating microRNAs, mitochondrial DNA (mtDNA), nutrient sensing, lipid metabolism, transcriptome profiles, long non-coding RNAs, protein metabolism, and neurotrophins. While these may not be biomarkers of aging per se, they have been used as

proxies of aging mechanisms since changes in these systems might be a consequence of cell dysfunction and aging. For instance, brain-derived neurotrophic factor (BDNF) is a thoroughly explored biomarker of aging in the literature, with studies showing that a decrease in BDNF levels is associated with many clinical features of aging, such as walking speed decline (Suire et al., 2017). Other known aging phenomena, such as synaptic alterations, DNA methylation, and development of age-related diseases (such as Alzheimer’s disease) have also been associated

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with decreased levels of BDNF or its precursor, proBDNF (Giuffrida et al., 2018; Oh et al.,

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2016), which suggests that this neurotrophic factor may be an important biomarker of aging across various conditions and sample populations.

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Changes in DNA repair have also been identified as possible biomarkers of aging (Xia et

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al., 2017), with studies suggesting an association between accelerated aging and a downregulation of DNA repair mechanisms. Accordingly, overexpression of DNA repair

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proteins is known to induce an elongation of the cellular life span (Dellago et al., 2012). Clinical research focused on these markers has thus far been limited to specific populations, such as

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patients with Down syndrome (Ahmed et al., 2018) and chronic obstructive pulmonary disease (Lakhdar et al., 2018), with fairly limited data on other age-related conditions. As mentioned previously, various other biomarkers of aging are also being explored by different research groups. For instance, transcriptome profiles have been used for the calculation

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of a “transcriptomic age” based on 11,908 genes differently expressed with age (Peters et al., 2015). Additionally, age-related phenotypes, such as dementia and decreased cognitive function, have been associated with molecular processes influenced by long non-coding RNAs (Grammatikakis et al., 2014) and circulating microRNAs (Halper et al., 2015; Margolis et al., 2017; Mengel-From et al., 2018; Noren Hooten et al., 2013; Zhang et al., 2015; Zheng and Xu,

2014). Finally, markers of protein and lipid metabolism, especially an increase in advanced glycosylation end products, have also been identified as biomarkers of aging (Dall'Olio et al., 2013; Harries et al., 2012). The relevance of each of these biomarkers in normal and pathological aging, as well as their potential cross-talk in different tissues, still warrants further research. In the next section, we will focus on alterations in common biomarkers of aging in samples of

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patients with BD.

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4. Accelerated biological aging in BD

A model proposed for the accelerated biological aging in BD can be seen in Figure 1.

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Based on evidence from the literature, we hypothesize that multiple biological systems interact

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with environmental triggers to induce premature aging in patients. A detailed review of specific

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markers and their relationship with BD is provided in the next couple of sections.

4.1 Telomere Shortening

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Telomeres are essential in protecting and maintaining the ends of eukaryotic DNA. These structures are located at the ends of chromosomes and feature a 5’-TTAGGG-3’ repeating sequence in humans. Hundreds or even thousands of these repeats protect DNA from losing valuable genetic information during each replication cycle, when a small portion of the ends of

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the chromosome are eroded. Over time, telomeres are shortened by the repetitive cycles of DNA replication. Due to this time-dependent shortening, telomeres have been consistently identified as biomarkers of aging in humans (Fasching, 2018). Accordingly, telomere shortening has been correlated with many disorders associated with aging, from osteoarthritis to Alzheimer’s disease (Kuszel et al., 2015; Liu et al., 2016).

Shortening of telomeres as a maker of premature aging in patients with BD has been somewhat controversial. Several studies have reported significant associations between telomere shortening and BD (Barbe-Tuana et al., 2016; Darrow et al., 2016; Elvsashagen et al., 2011; Lima et al., 2015; Rizzo et al., 2013; Simon et al., 2006; Vasconcelos-Moreno et al., 2017), in both early and late stages of BD (Barbe-Tuana et al., 2016). In contrast, other studies have found no association between BD and the length of one’s telomeres (Fries et al., 2017; Mamdani et al.,

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2015; Palmos et al., 2018), and a 2015 meta-analysis of 1,115 patients and healthy controls

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across seven different studies showed no significant association between BD and telomere length

of accelerated aging in BD as once assumed.

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(Colpo et al., 2015). This provided evidence that telomere length may not be as strong a marker

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In an attempt to address the uncertainty surrounding telomere length in BD, a 2018 metaanalysis of 579 patients and 551 controls across ten different studies was performed, and it

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suggested that telomere length is, in fact, significantly shortened in BD patients compared to healthy controls (Huang et al., 2018). This association was shown to be true regardless of the

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patient's mood state at the time of the study or the method used to measure their telomeres. Of additional interest is the difference in the length of telomeres of siblings of BD patients, who are known to be at higher risk for the onset of the disorder. One study indicated that telomere length is shorter in both patients with BD and their unaffected siblings, suggesting that there may be a

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genetic connection between shorter telomeres and risk for development of BD (VasconcelosMoreno et al., 2017). The variety of conclusions drawn from both individual studies and meta-analyses on

telomere length as a biomarker of aging suggests that there is still uncertainty and room for further research in the field. In this context, important factors that are associated with both BD

and telomere shortening should be carefully considered in study design. For example, BD has been repeatedly associated with obesity, which has also been shown to correlate negatively with telomere length (Bortolato et al., 2017; Gielen et al., 2018; Muezzinler et al., 2014; Zhao et al., 2016b). Additionally, smoking has been shown to be associated with BD, which has also been negatively correlated with telomere length (Astuti et al., 2017; Jackson et al., 2015). Finally, of special importance in the context of BD is its association between chronic stress, which has been

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commonly associated with BD and telomere shortening (Mathur et al., 2016). Specifically, this

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suggests that chronic stress could be a confounding variable that both increases risk of BD and shortens telomeres through different mechanisms.

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Obesity, smoking, and chronic stress are just a few of the many factors that have been

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associated with both shortened telomeres and BD; others include childhood trauma, drug use, and prenatal factors (Levandowski et al., 2016; Li et al., 2017; Marangoni et al., 2018; Van den

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Bergh et al., 2017). While some of the previously mentioned studies controlled for some of these variables (Barbe-Tuana et al., 2016; Darrow et al., 2016; Elvsashagen et al., 2011; Fries et al.,

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2017; Palmos et al., 2018; Rizzo et al., 2013; Simon et al., 2006; Vasconcelos-Moreno et al., 2017), many did not (Colpo et al., 2015; Lima et al., 2015; Mamdani et al., 2015), and none controlled for all of these variables at once. This suggests that some of these factors, along with treatment with mood stabilizers and other medications, may be confounding the outcomes of the

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studies discussed earlier. Clearly, additional exploration of the relationship between such factors and telomere shortening in the context of BD is needed to fully understand their relationship.

4.2 Oxidative Stress

Oxidative stress is defined as an imbalance between the production of free radicals and the system’s ability to remove these reactive species. By definition, free radicals are species that contain unpaired electrons. Possessing unpaired electrons makes free radicals highly reactive, which in turn causes them to interact with non-radicals to form a stable state (Betteridge, 2000). Formation of this stable state creates additional free radicals as byproducts, which then interact with other macromolecules in the cells. This cycle leads to cumulative damage to proteins,

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mitochondria, lipids, and nucleic acids, ultimately causing cellular dysfunction and eventually

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cell death.

Oxidative stress has been identified as a key player in the chronological aging process

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(Droge and Schipper, 2007; Golden et al., 2002; Poljsak et al., 2013; Starr et al., 2008). The

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“Oxidative Stress Theory of Aging” hypothesizes that the accumulation of damage caused by oxidative stress results in organisms’ overall aging. Current research shows a positive correlation

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between an organism’s metabolic rate and their production of reactive oxygen species (ROS), which may result in a shorter life span (Finkel and Holbrook, 2000). Specifically, there are two

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main factors that allow for the accumulation of oxidative damage associated with aging: (i) a reduction of antioxidant defense mechanisms, and (ii) age-associated mitochondrial changes (Gemma et al., 2007; Poljsak et al., 2013). Less antioxidant defense mechanisms are available in aging brains, which makes the brain more susceptible to oxidative damage (Gemma et al., 2007).

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Evidence of this includes an age-related increase of damage and mutations in mtDNA. As a consequence, mitochondria found in aging organisms are typically larger, less efficient, and less abundant (Cui et al., 2012; Poljsak et al., 2013). In addition, aging organisms are known to have an increased amount of ineffective autophagy systems, which function to remove dysfunctional mitochondria. As a consequence, the decreased amount of antioxidant defense mechanisms and

increased amount of free radicals may ultimately cause aging-related damage to the cell and organism. Accelerated aging in BD caused by oxidative stress has been suggested by several studies focused on the pathophysiology of the disorder (Andreazza et al., 2008; Berk et al., 2011; Brown et al., 2014; Frey et al., 2007; Steckert et al., 2010). Overall, significant differences between patients and controls have been reported in multiple oxidative stress markers, such as glutathione

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peroxidase (GPx), 8-oxo-2'-deoxyguanosine (8-oxodG), 8-oxo-7,8-dihydroguanosine (8-

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oxoGuo), lipid peroxidation hydroperoxides (LPH), glutathione S-transferase (GST), glutathione reductase (GR), 3-nitrotyrosine (3-NT), protein carbonyl (PC), and thiobarbituric acid reactive

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substances (TBARS). Prominent findings include a reduction of GPx levels (Vasconcelos-

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Moreno et al., 2017), although not in all populations (Andreazza et al., 2008), increased levels of 8-oxodG and 8-oxoGuo, which are markers of DNA and RNA oxidation damage, respectively

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(Jorgensen et al., 2013; Munkholm et al., 2015), and increased levels of lipid peroxidation in BD patients compared healthy controls (Andreazza et al., 2015). In addition, increased levels of GST

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and GR have also been reported in patients at a late stage of illness progression (Andreazza et al., 2009), although non-significant findings have also been reported for these two markers (Gawryluk et al., 2011; Vasconcelos-Moreno et al., 2017). Similarly, mixed results for 3-NT and PC levels have also been found (Andreazza et al., 2015; Andreazza et al., 2009; Kapczinski et

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al., 2011). TBARS, a byproduct of lipid peroxidation, has also been found to be higher in BD patients during mania or depression when compared to controls and to BD patients in euthymia (Kapczinski et al., 2011). Of note, the consequences of the age-related oxidative stress damage may also extend beyond harming macromolecules. Oxidative stress can also affect telomeres by forming an 8‐

oxodG at the guanine triplet in their sequence. This formation may play a role in the acceleration of telomere shortening in BD (Barbe-Tuana et al., 2016; Kawanishi and Oikawa, 2004), as discussed in the details in the previous section. In addition, LPH damages myelin due to its high amount of polyunsaturated fatty acid side chains, which can cause reductions in the transmission of electrical impulses (Versace et al., 2014). Finally, a negative correlation between TBARS and

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potentially accelerating aging processes (Kapczinski et al., 2008).

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BDNF has also been reported in patients with BD, thus reducing neuroplasticity mechanisms and

4.3 Inflammation

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When discussing inflammation in the context of psychiatric disorders, chronic low-level

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inflammation is the most commonly considered type of inflammation (Pahwa and Jialal, 2019). The clinical markers of such chronic low-level inflammation include a general feeling of illness

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(“sickness behavior”) and increased white blood cell, fibrinogen, and high-sensitivity C-reactive protein levels (Pietzner et al., 2017). Many life-altering conditions have been associated with

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inflammation, from arthritis to cancer to heart disease (Andrejeva and Rathmell, 2017; Yang et al., 2016; Zhao et al., 2016a). Clearly, inflammation has wide reaching effects both within and outside psychiatric disorders and a greater understanding of the phenomena will ultimately lead to better clinical practices.

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Not surprisingly, inflammation has been associated with BD by many studies and

research groups (Fries et al., 2019b). Inflammatory changes in both the central and peripheral nervous systems have been repeatedly observed in patients with BD, indicating that the association is not isolated to one part of the body (Fries et al., 2019b). Importantly, inflammation has also been proposed as an important biomarker of aging (Sayana et al., 2017). This is true in

both so-called “successful” and “unsuccessful” aging communities; for instance, studies of semisupercentenarians and of Alzheimer’s patients have all reported increased markers of inflammation (Arai et al., 2015; Holmes, 2013). In fact, age-related decrease in lamin B and agerelated redox imbalance (discussed in details in the previous section) can both upregulate proinflammatory markers and lead to chronic low-level inflammation (Chen et al., 2015; Chung et al., 2009).

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The research associating BD and inflammation is extensive; however, studies

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simultaneously linking inflammation, BD, and aging are limited. Rizzo and colleagues (2013) have shown an increase in T-cell senescence as a marker of aging in BD (Rizzo et al., 2013). In

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addition, another study has reported a link between atopy and eosinophil function, BD, and

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neuroprogression (Panizzutti et al., 2015). Specifically, increased eosinophil levels indicate increased inflammation in tissues, and their association with both BD and neuroprogression (an

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indirect indication of accelerated aging) offers strong evidence for inflammation as a biomarker of aging in BD. Of note, another study has shown similar results, suggesting that patients with

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BD are more likely to develop a pro-inflammatory state connected to neuroprogression (van den Ameele et al., 2018).

To further address the issue of accelerated aging in BD, the field must take into account both genetic and environmental factors as well as the relationships between multiple markers of

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aging. A study by the International Consortium on Lithium Genetics has suggested that genes related to the immune system, including the HLA antigen complex and inflammatory cytokines, may have an effect on BD patients’ response to lithium treatment (Amare et al., 2018). This indicates that inflammation may not only be a biomarker of aging in patients with BD but also a potential biomarker of response to treatment. In fact, the utility of anti-inflammatory agents in

the treatment of BD, particularly bipolar depression, has been suggested by many studies (Colpo et al., 2018; Rosenblat et al., 2016). Another study of particular interest suggests that obesity may moderate the relationship between certain markers of inflammation and BD, suggesting that environmental factors should be carefully considered in the study of inflammation as a biomarker of aging in BD (Yamagata et al., 2018). In fact, obesity and diabetes mellitus are highly prevalent in BD (Calkin et al., 2013;

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Charles et al., 2016; Reilly-Harrington et al., 2018), both of which include a derailment of the

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glucose metabolism as part of their mechanisms (Charles et al., 2016). Interestingly, the

hypoglycemic agent metformin has been shown to improve chronic inflammation through the

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improvement of metabolic parameters and direct inhibition of inflammatory pathways (Saisho,

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2015), and this same agent has been proposed as an anti-aging molecule by multiple studies (Barzilai et al., 2016; Fahy et al., 2019; Glossmann and Lutz, 2019). Metformin has also been

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shown to be an effective add-on medication in patients with mood disorders while acting on the same molecular targets of caloric restriction (a known anti-aging strategy) (Calkin et al., 2013;

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Grigolon et al., 2019; Hiluy et al., 2019), suggesting it as a promising drug in this population. Finally, research into the relationship between chronic low-grade inflammation, the microbiome of the human gut, and BD has the potential to greatly change patient care (Nguyen et al., 2018).

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5. Emerging biomarkers of aging 5.1 Epigenetic Aging Methylation of the DNA most commonly occurs on cytosines, where a methyl group is

incorporated to the fifth carbon. This modification then typically interferes with the structure of the DNA and may inhibit transcription. DNA methylation has been used to study aging in a

variety of conditions, from cancer to dementia (Dugue et al., 2018; Raina et al., 2017). More specifically, studies have shown that chronological age can be successfully predicted by DNA methylation with the so-called “epigenetic clocks” (Jung et al., 2017). Accordingly, several clocks using combinations of CpG sites in multiple tissues have been proposed (Jung et al., 2017). The plethora of contexts in which epigenetic aging has been studied indicates the importance of this marker in the understanding of the biology of aging in BD. Specifically,

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patients with BD have been shown to present an accelerated epigenetic aging in blood compared

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to controls, with significant correlations found between DNA methylation and mtDNA copy number (Fries et al., 2017). Although no differences have been found in the cerebellum of

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patients (Fries et al., 2017), an epigenetic aging acceleration has also been detected in post-

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mortem hippocampus of patients with BD compared with controls (Fries et al., 2019a), suggesting the relevance of such mechanisms in brain tissue. These studies offer evidence to the

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validity of DNA methylation as a biomarker of accelerated aging in BD. In considering a new potential biomarker of aging, such as the epigenetic clock, it is

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important to consider the environmental factors that could contribute to its alteration. One important environmental factor in BD is the history of childhood trauma, which has been linked to both the prevalence and the severity of the disorder (Agnew-Blais and Danese, 2016). Interestingly, according to a recent systematic review, most genome-wide studies of DNA

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methylation detail significant differences between the methylation of DNA in those with and without childhood trauma (Nothling et al., 2019). This suggests that any study of DNA methylation as a biomarker of aging in BD should ideally take into account the possible confounding influence of childhood trauma. Another important environmental factor in BD is the experience of psychosocial stress, which has also been linked to both the prevalence and the

severity of the disorder (Alloy et al., 2005). Similar to childhood trauma, psychosocial stress has been shown to have a significant effect on DNA methylation outside the context of BD (Unternaehrer et al., 2012), suggesting it as another possible confounding influence on DNA methylation findings in BD.

5.2 Mitochondrial Copy Number

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The mtDNA encodes genes essential for the functioning of the mitochondria, such as

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energy generation and the production of transfer and ribosomal RNA. The mtDNA is self-

replicating, and its amount present at a given time is referred to as the mtDNA copy number.

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MtDNA copy number is currently being investigated as a biological marker and has been

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associated with both aging and diseases of aging (Revesz et al., 2018; Zhang et al., 2017). Specifically, there is evidence to suggest a negative relationship between age and mtDNA copy

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number in different populations (Mengel-From et al., 2014; Verhoeven et al., 2018; Zole and Ranka, 2019). Zole and colleagues (2017) found a significant decrease in mtDNA copy number

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when comparing a group of subjects aged 60-89 to a group aged 20-59 (Zole et al., 2018). Additionally, restoring the mtDNA copy number has been shown to recover mitochondrial function and slow cellular aging (Foote et al., 2018). Comparisons to other markers of aging have been performed to bring validity to this

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marker. For example, a positive relationship between telomere length and mtDNA copy number has been demonstrated (Kim et al., 2013; Verhoeven et al., 2018). Additionally, an increased mtDNA copy number has been associated with poor mitochondrial health overall, which may reflect enhanced mitochondrial oxidative damage (Chang et al., 2014; Hosnijeh et al., 2014; Verhoeven et al., 2018).

Not surprisingly, evidence suggests that mtDNA copy number regulation may also be involved in the pathophysiology of BD (Wang et al., 2018). As discussed earlier, oxidative stress can cause an increase in the number of mutations in the mtDNA. Polymerase gamma (POLG) is the only known enzyme that can replicate mtDNA and is also the mitochondrial protein that is most susceptible to oxidative damage (Chang et al., 2014). Kakiuchi and colleagues (2005) found that POLG expression levels were significantly higher in patients with BD compared to

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healthy controls and suggested that this increase may be indicative of counterbalancing

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mechanisms for the age-dependent decrease of mtDNA in patients with BD (Kakiuchi et al., 2005). Most significantly, patients with BD have been shown to present significantly lower

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mtDNA copy number (Chang et al., 2014; Kageyama et al., 2018). In looking at mood-specific

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states, Wang and colleagues (2018) found that, in comparison to healthy controls, BD patients in depressed and manic states had significantly lower mtDNA copy numbers (Wang et al., 2018).

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Furthermore, Chang and colleagues (2014) reported that mtDNA damage is positively correlated with age and that patients with BD had significantly higher mitochondrial oxidative damage than

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controls (Chang et al., 2014). Importantly, while some studies found no differences in mtDNA copy number between patients with BD and controls (de Sousa et al., 2014; Scaini et al., 2017), some have found that patients had a higher mtDNA number than controls (Fries et al., 2017). Although the relevance of such mixed findings have yet to be resolved, the ways in which these

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studies vary may provide some insight into these discrepancies. For instance, while there was a range of samples sizes within the studies considered, most of them were small in number. The studies also varied in regards to conditions related to the blood collection, such as time of day and fasting status. The inclusion and exclusion criteria also varied for each study, with some taking types of treatment patients had undergone prior to the study into account and some not.

Finally, there is evidence that early life stress can increase the mtDNA copy number in adults, suggesting this as an important confounding variable in these studies (Tyrka et al., 2016).

6. Clinical Implications As previously discussed, accelerated aging may have many clinical consequences, from cognitive decline to the development of life-threatening diseases. The accelerated aging in BD

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outlined in this review offers possible targets for new treatments for the disorder. This is an

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exciting insight when considering the prevalence and severity of the disorder. In this section, we will explore clinical implications associated with the three main biomarkers of accelerated aging

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outlined above (telomere shortening, increased oxidative stress, and inflammation).

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When considering clinical connections between telomere length shortening and BD, the effects of lithium may be of interest for further investigation. Lithium has been shown to

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normalize both Tert expression and telomerase activity in the hippocampi of rats that had previously had dysregulated telomerase, indicating that it might have a restorative effect on

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telomere length (Wei et al., 2015). This seems to be particularly true in patients that are clinically responsive to the treatment, with evidence of an increase in telomere length in response to the drug in patients who are clinically responsive to lithium compared to those who are not clinically responsive (Martinsson et al., 2013; Squassina et al., 2016). This illustrates the possibility that

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telomere length may not be a homogenous biomarker of aging in BD. These relationships between lithium treatment and telomere length suggest that treatment may be an important confounding variable in the current studies of telomere length as a biomarker of aging in BD. Given that oxidative stress may be an important player in the accelerated aging seen in BD, antioxidants may provide important treatment opportunities. In 2018, a double-blind

controlled clinical trial showed that, compared to placebo, the antioxidant coenzyme Q10 was able to significantly improve symptoms of depression, offering evidence that antioxidants may be an avenue by which to treat the depressive episodes associated with BD. Of note, the conclusions of this study were limited by the fact that coenzyme Q10 is also an antiinflammatory (Mehrpooya et al., 2018). A similar study on aspirin and N-acetylcysteine showed similar results, but had a similar limitation in that these molecules serve as both anti-

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inflammatory and antioxidant agents (Bauer et al., 2018). Overall, while these studies offer

effects of reducing oxidative stress on the treatment of BD.

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interesting insights into new ways to treat BD, further research is needed to determine the precise

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Finally, inflammation also seems to be a logical target in the clinical treatment of the

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disorder. A 2017 meta-analysis on the use of anti-inflammatory treatments for mood disorders suggests that they may have a positive effect on both the manic and depressive symptoms of

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patients with BD (Husain et al., 2017). Interestingly, a more recent original study looked at a large population size of over 1.6 million patients and determined that continued use of low-dose

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aspirin was associated with decreased incidence of BD (Kessing et al., 2019). This offers evidence that treating the inflammation associated with accelerated aging may be an important target in the treatment of BD. While anti-inflammatories offer a promising new avenue for the

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treatment of BD, further research is needed to confirm currently limited findings.

7. Conclusion In summary, this review has highlighted evidence of premature aging in BD, general

biomarkers of aging, and potential mechanisms involved in the accelerated biological aging in BD. Moreover, our results have underscored several aspects of research surrounding aging in BD

that should be further explored. Specifically, additional studies investigating telomere length, oxidative stress, inflammatory markers, DNA methylation, and mtDNA copy number within the context of accelerated aging in BD are needed to refute or confirm the relationships observed in the current literature. Furthermore, additional studies should be mindful of environmental factors, such as childhood trauma or psychological stress, which could have confounding effects on biomarkers of aging. Overall, the findings of this review strongly suggest BD as an

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accelerated aging disease as evidenced by both clinical and biological variables.

8. Acknowledgments This study was supported in part by the UTHealth Consortium on Aging, The University of Texas Houston Retiree Organization (UTHRO), and the Louis A. Faillace, MD Department of Psychiatry and Behavioral Sciences, The University of Texas Health Science Center at Houston (UTHealth). Translational Psychiatry Program (USA) is funded by the Louis A. Faillace, MD Department of Psychiatry and Behavioral Sciences, McGovern Medical School, UTHealth.

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Center of Excellence on Mood Disorders (USA) is funded by the Pat Rutherford Jr. Chair in

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Psychiatry, John S. Dunn Foundation and Anne and Don Fizer Foundation Endowment for

Depression Research. Translational Psychiatry Laboratory (Brazil) is funded by grants from

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Coordenação de

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Aperfeiçoamento de Pessoal de Nível Superior (CAPES), Fundação de Amparo à Pesquisa e Inovação do Estado de Santa Catarina (FAPESC), Instituto Cérebro e Mente and University of

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Southern Santa Catarina (UNESC). GRF is supported by a career development grant from the UTHealth Center for Clinical and Translational Sciences (CCTS). JQ is a 1A CNPq Research

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Fellow. The authors declare no competing interests, and funding body had no role in the design of the study or decision to publish.

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Declarations of interest: none.

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Figure captions

Figure 1. Schematic model for the accelerated biological aging in bipolar disorder. The blue dashed line represents the time-dependent trajectory of normal aging. Environmental factors, including lifetime chronic stress exposure, mood episodes, and lifestyle factors and habits (such as diet, smoking, exercise and others)can all contribute to speeding of the normal aging process

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and promote an accelerated aging phenotype (red dashed line). Such premature aging processes

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can be detected in vivo through a plethora of biomarkers, such as telomere length, inflammatory molecules, oxidative stress, mitochondrial DNA (mtDNA) copy number, DNA methylation, and

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genetic markers, which may also interact with environmental factors to further foster biological

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aging processes. The cross-talk between these multiple biological mechanisms and environmental factors is believed to contribute to the premature aging in patients with bipolar

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disorder and ultimately speed up the onset of age-related clinical signs and conditions.

Table 1. Clinical markers of accelerated aging in bipolar disorder are varied across and within different systems. Variable

Direction of change in bipolar disorder

Reference

Cognitive Markers

Executive Function

↓

(Seelye et al., 2019)

Cognitive Control

↓

(Seelye et al., 2019)

Information Processing Speed

↓

(Gildengers et al., 2007)

Rate of Metabolic Imbalance

↑

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↑

(Coello et al., 2019; Toma et al., 2019) (Ayerbe et al., 2018)

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Rate of Hypertension

(Moreira et al., 2017; Moreira et al., 2019)

↑

(Diniz et al., 2017)

↑

(Arnone et al., 2009; Hibar et al., 2016)

Grey Matter Volume of the Cerebellum

↓

(Hallahan et al., 2011)

Grey Matter Volume of the Hippocampus

↓

(Cao et al., 2017; Cao et al., 2016)

Prefrontal Cortex Volume

↓

(Almeida et al., 2009; Blumberg et al., 2006)

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Rate of Dementia Neuroanatomical Ventricular Markers size

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Cardiovascular ↑ Risk Score

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Disease Markers

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Type